Growth factor receptors are overexpressed in many cancers and their presence correlates with poor prognosis. Activation of growth factors signaling pathways results in increased proliferation, motility and resistance to chemo - and radiation therapies. It has been shown recently that the resistance of tumor cells to therapy aimed at blocking individual growth factor signaling pathways may be caused by cross-talk with another growth factor pathway. For example, activation of IGF pathway interferes with anti-EGF pathway therapy. Only very recently, appropriate software tools and sufficient computer power have become available that allow a quantitative computational exploration of signaling pathways as complex as the EGF/IGF pathway. Complication of the growth factor signaling system makes the empirical approach to targeted therapy quite inefficient. We propose to create a detailed computational model signaling pathways based on available literature data and experimentally verify its accuracy using quantitative biochemistry. The model will allow simulation of cellular response to growth factors and computational (in silico) exploration of possible therapeutic interventions aiming at selective blocking of these pathways and provide means for optimization of molecular therapy for tumors overexpressing growth factor receptors, e.g. IGF and EGF receptor families.